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Home > Standards & Guidances > Methodological Guide

ENCePP Guide on Methodological Standards in Pharmacoepidemiology



4.4.1. Pragmatic trials

Randomised clinical trials (RCTs) are considered the gold standard for demonstrating the efficacy of medicinal products and for obtaining an initial estimate of the risk of adverse outcomes. However, as is well understood, these data are often not necessarily indicative of the benefits, risks or comparative effectiveness of an intervention when used in clinical practice populations. The IMI GetReal Glossary defines a pragmatic clinical trial (PCT) as ‘a study comparing several health interventions among a randomised, diverse population representing clinical practice, and measuring a broad range of health outcomes. There is no distinct demarcation between these two types of trial rather they represent a continuum of design with PCTs being focused on evaluating benefits and risks of treatments in patient populations and settings more representative of routine clinical practice. 


To ensure generalizability, pragmatic trials should represent the patients to whom the treatment will be applied, for instance, inclusion criteria would be broad (e.g. allowing co-morbidity, co-medication, wider age range, etc.), the follow-up would be minimized and allow for treatment switching etc.  In this sense, PCTs may be seen to represent a sub-category of large simple trials.


Pragmatic explanatory continuum summary (PRECIS): a tool to help trial designers (CMAJ 2009; 180: E45-57) is a tool to support pragmatic trial designs and define the degree of pragmatism.  The PRECIS tool has been further refined and now comprises nine domains each scored on a 5 point Likert scale ranging from very explanatory to very pragmatic with an exclusive focus on the issue of applicability (The PRECIS-2 tool: designing trials that are fit for purpose. BMJ 2015; 350: h2147).  A checklist and additional guidance is also provided in Improving the reporting of pragmatic trials: an extension of the CONSORT statement (BMJ 2008; 337 (a2390): 1-8).


Individual Chapters:


1. General aspects of study protocol

2. Research question

3. Approaches to data collection

3.1. Primary data collection

3.2. Secondary use of data

3.3. Research networks

3.4. Spontaneous report database

3.5. Using data from social media and electronic devices as a data source

3.5.1. General considerations

4. Study design and methods

4.1. General considerations

4.2. Challenges and lessons learned

4.2.1. Definition and validation of drug exposure, outcomes and covariates Assessment of exposure Assessment of outcomes Assessment of covariates Validation

4.2.2. Bias and confounding Choice of exposure risk windows Time-related bias Immortal time bias Other forms of time-related bias Confounding by indication Protopathic bias Surveillance bias Unmeasured confounding

4.2.3. Methods to handle bias and confounding New-user designs Case-only designs Disease risk scores Propensity scores Instrumental variables Prior event rate ratios Handling time-dependent confounding in the analysis

4.2.4. Effect modification

4.3. Ecological analyses and case-population studies

4.4. Hybrid studies

4.4.1. Pragmatic trials

4.4.2. Large simple trials

4.4.3. Randomised database studies

4.5. Systematic review and meta-analysis

4.6. Signal detection methodology and application

5. The statistical analysis plan

5.1. General considerations

5.2. Statistical plan

5.3. Handling of missing data

6. Quality management

7. Communication

7.1. Principles of communication

7.2. Guidelines on communication of studies

8. Legal context

8.1. Ethical conduct, patient and data protection

8.2. Pharmacovigilance legislation

8.3. Reporting of adverse events/reactions

9. Specific topics

9.1. Comparative effectiveness research

9.1.1. Introduction

9.1.2. General aspects

9.1.3. Prominent issues in CER Randomised clinical trials vs. observational studies Use of electronic healthcare databases Bias and confounding in observational CER

9.2. Vaccine safety and effectiveness

9.2.1. Vaccine safety General aspects Signal detection Signal refinement Hypothesis testing studies Meta-analyses Studies on vaccine safety in special populations

9.2.2. Vaccine effectiveness Definitions Traditional cohort and case-control studies Screening method Indirect cohort (Broome) method Density case-control design Test negative design Case coverage design Impact assessment Methods to study waning immunity

9.3. Design and analysis of pharmacogenetic studies

9.3.1. Introduction

9.3.2. Identification of genetic variants

9.3.3. Study designs

9.3.4. Data collection

9.3.5. Data analysis

9.3.6. Reporting

9.3.7. Clinical practice guidelines

9.3.8. Resources

Annex 1. Guidance on conducting systematic revies and meta-analyses of completed comparative pharmacoepidemiological studies of safety outcomes